Gas Exchange: Humans Flashcards
Explain the essential features of the alveolar epithelium that make it
adapted as a surface for gas exchange:
- Flattened cells / 1 cell thick → short diffusion distance
- Folded → large surface area
- Permeable → allows diffusion of O2 / CO2
- Moist → gases can dissolve for diffusion
- Good blood supply from large network of capillaries→
maintains concentration gradient
Describe how gas exchange occurs in the lungs:
- Oxygen diffuses from alveolar air space into blood down its concentration gradient
- Across alveolar epithelium then across capillary endothelium
Explain the importance of ventilation:
- Brings in air containing higher conc. of oxygen & removes air with lower conc. of oxygen
- Maintaining concentration gradients
Inspiration (breathing in):
- Diaphragm muscles contract → flattens
- External intercostal muscles contract, internal
intercostal muscles relax (antagonistic) →
ribcage pulled up / out - Increasing volume and decreasing pressure
(below atmospheric) in thoracic cavity - Air moves into lungs down pressure gradient
Expiration (breathing out):
- Diaphragm relaxes → moves upwards
- External intercostal muscles relax, internal
intercostal muscles may contract → ribcage
moves down / in - Decreasing volume and increasing pressure
(above atmospheric) in thoracic cavity - Air moves out of lungs down pressure gradient
Suggest why expiration is normally passive at rest:
- Internal intercostal muscles do not normally need to contract
- Expiration aided by elastic recoil in alveoli
Suggest how different lung diseases reduce the rate of gas exchange:
- Thickened alveolar tissue (eg. fibrosis) → increases diffusion distance
- Alveolar wall breakdown → reduces surface area
- Reduce lung elasticity → lungs expand / recoil less → reduces concentration gradients of O2 / CO2
Suggest how different lung diseases affect ventilation:
- Reduce lung elasticity (eg. fibrosis - build-up of scar tissue) → lungs expand / recoil less
○ Reducing volume of air in each breath (tidal volume)
○ Reducing maximum volume of air breathed out in one breath (forced vital capacity) - Narrow airways / reduce airflow in & out of lungs (eg. asthma - inflamed bronchi)
○ Reducing maximum volume of air breathed out in 1 second (forced expiratory volume) - Reduced rate of gas exchange → increased ventilation rate to compensate for reduced oxygen in blood
Suggest why people with lung disease experience fatigue:
Cells receive less oxygen → rate of aerobic respiration reduced → less ATP made
Suggest how you can analyse and interpret data to the effects of pollution,
smoking and other risk factors on the incidence of lung disease:
- Describe overall trend → eg. positive / negative correlation between risk factor and incidence of disease
- Manipulate data → eg. calculate percentage change
- Interpret standard deviations → overlap suggests differences in means are likely to be due to chance
- Use statistical tests → identify whether difference / correlation is significant or due to chance
○ Correlation coefficient → examining an association between 2 sets of data
○ Student’s t test → comparing means of 2 sets of data
○ Chi-squared test → for categorical data
Suggest how you can evaluate the way in which experimental data led to
statutory restrictions on the sources of risk factors:
- Analyse and interpret data as above and identify what does and doesn’t support statement
- Evaluate method of collecting data
○ Sample size → large enough to be representative of population?
○ Participant diversity eg. age, sex, ethnicity and health status → representative of population?
○ Control groups → used to enable comparison?
○ Control variables eg. health, previous medications → valid?
○ Duration of study → long enough to show long-term effects? - Evaluate context → has a broad generalisation been made from
Explain the difference between correlations and causal relationships:
- Correlation = change in one variable reflected by a change in another - identified on a scatter diagram
- Causation = change in one variable causes a change in another variable
- Correlation does not mean causation → may be other factors involved